New Online Risk Prediction Tool for Diabetic Nephropathy Patients
At the 26th European Meeting on Hypertension and Cardiovascular Protection in Paris, the ALICE-PROTECT study introduced an online risk prediction tool for diabetic nephropathy. This tool utilizes Bayesian modeling to predict the 2-year cardiovascular event risk for patients with type 2 diabetes and diabetic nephropathy. The study observed patient outcomes, including blood pressure and proteinuria levels, to optimize treatment strategies. Explore the tool and its implications for managing diabetic nephropathy effectively.
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26thEuropean Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 ALICE-PROTECT Study Yields Online Risk Prediction Tool in Diabetic Nephropathy From ESH 2016 | LB 1: Jean-Pierre Fauvel, MD CHU Lyon, H pital E Herriot, Lyon, France Infomedica Conference Coverage* of 26thEuropean Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 * Infomedica is an independent medical education provider that produces medical information to healthcare professionals through conference coverage and online educational programs and activities. Powered by Infomedica
26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 Overview Online risk prediction tool created to aid optimizing treatment of diabetic nephropathy ALICE-PROTECT study data of patients with type 2 diabetes (T2D) and diabetic nephropathy used for Bayesian modeling Online tool predicts 2-year risk of cardiovascular (CV) event Access for online calculator: https://www.hed.cc/?s=cvevent&t=CV%20Event Powered by Infomedica 26th European Meeting on Hypertension and Cardiovascular Protection
26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 ALICE-PROTECT Study Prospective, observational study Primary outcome: number of patients at 2 years with blood pressure <130/80 mmHg and proteinuria <0.5 g daily 986 patients, mean age 70 years, mean eGFR 42 ml/min/1.73 m2, 66% patients had proteinuria >1 g daily 630 patients alive at 2 years; 39 patients had CV event during Year 1; 26 patients died from CV cause Reference: Joly D et al. Diabetes Res Clin Pract 2015 Powered by Infomedica 26th European Meeting on Hypertension and Cardiovascular Protection
26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 Proportion of Patients with a Cardiovascular Event in ALICE-PROTECT At least one CV Event 24.1 Acute Coronary syndrome 8.4 Peripheral vascular event 5.5 Stroke 3.4 Heart Failure 11 0 10 20 30 % of the population Powered by Infomedica 26th European Meeting on Hypertension and Cardiovascular Protection
26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 Variables in Bayesian Model Patient Characteristics Age, sex, body mass index, blood pressure, ethnicity, smoking habits Medical History Stroke, sleep apnea, peripheral arterial disease, ischemic heart disease, heart failure, diabetes duration, hypertension duration, retinopathy Powered by Infomedica 26th European Meeting on Hypertension and Cardiovascular Protection
26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 Variables in Bayesian Model Biology eGFR, potassium, low-density lipoprotein cholesterol, HbA1c, proteinuria, hemoglobin Treatment Renin angiotensin system blockers, ASE, insulin, statin, diuretics, antithrombotic agent Powered by Infomedica 26th European Meeting on Hypertension and Cardiovascular Protection
26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 Variables in Bayesian Model Created Bayesian network to simulate data, using original data from ALICE-PROTECT study Simulation calibrated with 2000 simulated individual data, 1000 with and 1000 without a CV event; multiple links found between variables Bayesian network mimics usual medical thinking by physicians, analyzes large number of variables Used increasingly as diagnostic tools for medical decision making Powered by Infomedica 26th European Meeting on Hypertension and Cardiovascular Protection
26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 ALICE-PROTECT Study Yields Online Risk Prediction Tool in Diabetic Nephropathy From ESH 2016 | LB 1: Jean-Pierre Fauvel, MD CHU Lyon, H pital E Herriot, Lyon, France Infomedica Conference Coverage* of 26th European Meeting on Hypertension and Cardiovascular Protection Paris (France), June 10-13, 2016 * Infomedica is an independent medical education provider that produces medical information to healthcare professionals through conference coverage and online educational programs and activities. Powered by Infomedica
